In many situations, it is useful to construct a three-dimensional (3D) model of an object when only a partial description of the object is available. In a typical situation, one or more two-dimensional (2D) images of the 3D object may be available, perhaps photographs taken from different viewpoints. A common method of creating a 3D model of a multi-featured object is to start with a base 3D model which describes a generic or typical example of the type of object being modeled, and then to add texture to the model using one or more 2D images of the object. For example, if the multi-featured object is a human face, a 3D “avatar” (i.e., an electronic 3D graphical or pictorial representation) would be generated by using a pre-existing, standard 3D model of a human face, and mapping onto the model a texture from one or more 2D images of the face. See U.S. Pat. No. 6,532,011 B1 to Francini et al., and U.S. Pat. No. 6,434,278 B1 to Hashimoto. The main problem with this approach is that the 3D geometry is not highly defined or tuned for the actual target object which is being generated.
A common variant of the above approach is to use a set of 3D base models and select the one that most resembles the target object before performing the texture mapping step. Alternatively, a single parameterized base model is used, and the parameters of the model are adjusted to best approximate to the target. See U.S. Pat. No. 6,556,196 B1 to Blanz et al. These methods serve to refine the geometry to make it fit the target, at least to some extent. However, for any target object with a reasonable range of intrinsic variability, the geometry of the model will still not be well tuned to the target. This lack of geometric fit will detract from the verisimilitude of the 3D model to the target object.
Conventional techniques typically also require that the 2D images being used for texturing the model be acquired from known viewpoints relative to the 3D object being modeled. This usually limits the use of such approaches to situations where the model is being generated in a controlled environment in which the target object can be photographed. Alternatively, resort may be had to human intervention to align 2D images to the 3D model to be generated. See U.S. Patent Publication No. 2002/0012454 to Liu et al. This manual step places a severe limit on the speed with which a 3D model can be generated from 2D imagery.
Accordingly, a need exists for an automated approach that systematically makes use of available 2D source data for a 3D object to synthesize an optimal 3D model of the object.